Stereoelectroencephalography in epilepsy, cognitive neurophysiology, and psychiatric disease: safety, efficacy, and place in therapy

Origami-inspired soft fluidic actuation for minimally invasive large-area electrocorticography

Electrocorticography is an established neural interfacing technique wherein an array of electrodes enables large-area recording from the cortical surface. Electrocorticography is commonly used for seizure mapping however the implantation of large-area electrocorticography arrays is a highly invasive procedure, requiring a craniotomy larger than the implant area to place the device. In this work, flexible thin-film electrode arrays are combined with concepts from soft robotics, to realize a large-area electrocorticography device that can change shape via integrated fluidic actuators. We show that the 32-electrode device can be packaged using origami-inspired folding into a compressed state and implanted through a small burr-hole craniotomy, then expanded on the surface of the brain for large-area cortical coverage. The implantation, expansion, and recording functionality of the device is confirmed in-vitro and in porcine in-vivo models. The integration of shape actuation into neural implants provides a clinically viable pathway to realize large-area neural interfaces via minimally invasive surgical techniques.

The surgical interval between robot-assisted SEEG and epilepsy resection surgery is an influencing factor of SSI

BACKGROUND

In recent years, the development of robotic neurosurgery has brought many benefits to patients, but there are few studies on the occurrence of surgical site infection (SSI) after robot-assisted stereoelectroencephalography (SEEG). The purpose of this study was to collect relevant data from robot-assisted SEEG over the past ten years and to analyze the influencing factors and economic burden of surgical site infection.

METHODS

Basic and surgical information was collected for all patients who underwent robot-assisted SEEG from January 2014 to December 2023. Logistic regression was used to analyze the factors influencing SSI according to different subgroups (radiofrequency thermocoagulation or epilepsy resection surgery).

RESULTS

A total of 242 subjects were included in this study. The risk of SSI in the epilepsy resection surgery group (18.1%) was 3.5 times greater than that in the radiofrequency thermocoagulation group (5.1%) (OR 3.49, 95% CI 1.39 to 9.05); this difference was statistically significant. SSI rates in the epilepsy resection surgery group were associated with shorter surgical intervals (≤ 9 days) and higher BMI (≥ 23 kg/m2) (6.1 and 5.2 times greater than those in the control group, respectively). Hypertension and admission to the intensive care unit (ICU) were risk factors for SSI in the radiofrequency thermocoagulation group. Patients with SSIs had $21,231 more total hospital costs, a 7-day longer hospital stay, and an 8-day longer postoperative hospital stay than patients without SSI.

CONCLUSIONS

The incidence of SSI in patients undergoing epilepsy resection after stereoelectroencephalography was higher than that in patients undergoing radiofrequency thermocoagulation. For patients undergoing epilepsy resection surgery, prolonging the interval between stereoelectroencephalography and epilepsy resection surgery can reduce the risk of SSI; At the same time, for patients receiving radiofrequency thermocoagulation treatment, it is not recommended to enter the ICU for short-term observation if the condition permits.

Beta-band power modulation in the human amygdala differentiates between go/no-go responses in an arm-reaching task

Objective. Traditionally known for its involvement in emotional processing, the amygdala's involvement in motor control remains relatively unexplored, with sparse investigations into the neural mechanisms governing amygdaloid motor movement and inhibition. This study aimed to characterize the amygdaloid beta-band (13-30 Hz) power between 'Go' and 'No-go' trials of an arm-reaching task.Approach. Ten participants with drug-resistant epilepsy implanted with stereoelectroencephalographic (SEEG) electrodes in the amygdala were enrolled in this study. SEEG data was recorded throughout discrete phases of a direct reach Go/No-go task, during which participants reached a touchscreen monitor or withheld movement based on a colored cue. Multitaper power analysis along with Wilcoxon signed-rank and Yates-correctedZtests were used to assess significant modulations of beta power between the Response and fixation (baseline) phases in the 'Go' and 'No-go' conditions.Main results. In the 'Go' condition, nine out of the ten participants showed a significant decrease in relative beta-band power during the Response phase (p⩽ 0.0499). In the 'No-go' condition, eight out of the ten participants presented a statistically significant increase in relative beta-band power during the response phase (p⩽ 0.0494). Four out of the eight participants with electrodes in the contralateral hemisphere and seven out of the eight participants with electrodes in the ipsilateral hemisphere presented significant modulation in beta-band power in both the 'Go' and 'No-go' conditions. At the group level, no significant differences were found between the contralateral and ipsilateral sides or between genders.Significance.This study reports beta-band power modulation in the human amygdala during voluntary movement in the setting of motor execution and inhibition. This finding supplements prior research in various brain regions associating beta-band power with motor control. The distinct beta-power modulation observed between these response conditions suggests involvement of amygdaloid oscillations in differentiating between motor inhibition and execution.

Voxeloc: A time-saving graphical user interface for localizing and visualizing stereo-EEG electrodes

BACKGROUND

Thanks to its unrivalled spatial and temporal resolutions and signal-to-noise ratio, intracranial EEG (iEEG) is becoming a valuable tool in neuroscience research. To attribute functional properties to cortical tissue, it is paramount to be able to determine precisely the localization of each electrode with respect to a patient's brain anatomy. Several software packages or pipelines offer the possibility to localize manually or semi-automatically iEEG electrodes. However, their reliability and ease of use may leave to be desired.

NEW METHOD

Voxeloc (voxel electrode locator) is a Matlab-based graphical user interface to localize and visualize stereo-EEG electrodes. Voxeloc adopts a semi-automated approach to determine the coordinates of each electrode contact, the user only needing to indicate the deep-most contact of each electrode shaft and another point more proximally.

RESULTS

With a deliberately streamlined functionality and intuitive graphical user interface, the main advantages of Voxeloc are ease of use and inter-user reliability. Additionally, oblique slices along the shaft of each electrode can be generated to facilitate the precise localization of each contact. Voxeloc is open-source software and is compatible with the open iEEG-BIDS (Brain Imaging Data Structure) format.

COMPARISON WITH EXISTING METHODS

Localizing full patients' iEEG implants was faster using Voxeloc than two comparable software packages, and the inter-user agreement was better.

CONCLUSIONS

Voxeloc offers an easy-to-use and reliable tool to localize and visualize stereo-EEG electrodes. This will contribute to democratizing neuroscience research using iEEG.

Stereoelectroencephalography: a review of complications and outcomes in a new Australian centre

BACKGROUND

Surgical management of refractory focal epilepsy requires preoperative localisation of the epileptogenic zone (EZ). To augment noninvasive studies, stereoelectroencephalography (SEEG) is being increasingly adopted as a form of intracranial monitoring.

AIMS

This study aimed to determine the rate of complications for patients undergoing SEEG and to report the success of SEEG with regard to EZ detection and seizure outcome following definitive surgery.

METHODS

A retrospective cohort design investigated all cases of SEEG at our institution. Surgical, anaesthetic and medical complications with subsequent epilepsy surgery and seizure outcome data were extracted from medical records. Multivariate logistic regression was used to investigate the relationship between both the number of electrodes per patient and the duration of SEEG recording with the rate of complications.

RESULTS

Sixty-four patients with 66 implantations were included. Headache was the most common complication (n = 54, 82%). There were no major surgical or medical complications. Two anaesthetic complications occurred. EZ localisation was successful in 63 cases (95%). Curative intent surgery was performed in 39 patients (59%) and 23 patients achieved an Engel class I outcome (59% of those undergoing surgery). The number of electrodes and duration of recording were not associated with complications.

CONCLUSIONS

No patients in our series experienced major surgical or medical complications and we have highlighted the challenges associated with neuroanaesthesia in SEEG. Our complication rates and seizure outcomes are equivalent to published literature indicating that this technique can be successfully established in newer centres using careful case selection. Standardised reporting of SEEG complications should be adopted.

MRI and CT Fusion in Stereotactic Electroencephalography (SEEG)

Epilepsy is a neurological disorder characterized by spontaneous recurrent seizures. While 20% to 30% of epilepsy cases are untreatable with Anti-Epileptic Drugs, some of these cases can be addressed through surgical intervention. The success of such interventions greatly depends on accurately locating the epileptogenic tissue, a task achieved using diagnostic techniques like Stereotactic Electroencephalography (SEEG). SEEG utilizes multi-modal fusion to aid in electrode localization, using pre-surgical resonance and post-surgical computer tomography images as inputs. To ensure the absence of artifacts or misregistrations in the resultant images, a fusion method that accounts for electrode presence is required. We proposed an image fusion method in SEEG that incorporates electrode segmentation from computed tomography as a sampling mask during registration to address the fusion problem in SEEG. The method was validated using eight image pairs from the Retrospective Image Registration Evaluation Project (RIRE). After establishing a reference registration for the MRI and identifying eight points, we assessed the method's efficacy by comparing the Euclidean distances between these reference points and those derived using registration with a sampling mask. The results showed that the proposed method yielded a similar average error to the registration without a sampling mask, but reduced the dispersion of the error, with a standard deviation of 0.86 when a mask was used and 5.25 when no mask was used.

Dissociable default-mode subnetworks subserve childhood attention and cognitive flexibility: Evidence from deep learning and stereotactic electroencephalography

Cognitive flexibility encompasses the ability to efficiently shift focus and forms a critical component of goal-directed attention. The neural substrates of this process are incompletely understood in part due to difficulties in sampling the involved circuitry. We leverage stereotactic intracranial recordings to directly resolve local-field potentials from otherwise inaccessible structures to study moment-to-moment attentional activity in children with epilepsy performing a flexible attentional task. On an individual subject level, we employed deep learning to decode neural features predictive of task performance indexed by single-trial reaction time. These models were subsequently aggregated across participants to identify predictive brain regions based on AAL atlas and FIND functional network parcellations. Through this approach, we show that fluctuations in beta (12-30 Hz) and gamma (30-80 Hz) power reflective of increased top-down attentional control and local neuronal processing within relevant large-scale networks can accurately predict single-trial task performance. We next performed connectomic profiling of these highly predictive nodes to examine task-related engagement of distributed functional networks, revealing exclusive recruitment of the dorsal default mode network during shifts in attention. The identification of distinct substreams within the default mode system supports a key role for this network in cognitive flexibility and attention in children. Furthermore, convergence of our results onto consistent functional networks despite significant inter-subject variability in electrode implantations supports a broader role for deep learning applied to intracranial electrodes in the study of human attention.

A Neurospheroid-Based Microrobot for Targeted Neural Connections in a Hippocampal Slice

Functional restoration by the re-establishment of cellular or neural connections remains a major challenge in targeted cell therapy and regenerative medicine. Recent advances in magnetically powered microrobots have shown potential for use in controlled and targeted cell therapy. In this study, a magnetic neurospheroid (Mag-Neurobot) that can form both structural and functional connections with an organotypic hippocampal slice (OHS) is assessed using an ex vivo model as a bridge toward in vivo application. The Mag-Neurobot consists of hippocampal neurons and superparamagnetic nanoparticles (SPIONs); it is precisely and skillfully manipulated by an external magnetic field. Furthermore, the results of patch-clamp recordings of hippocampal neurons indicate that neither the neuronal excitabilities nor the synaptic functions of SPION-loaded cells are significantly affected. Analysis of neural activity propagation using high-density multi-electrode arrays shows that the delivered Mag-Neurobot is functionally connected with the OHS. The applications of this study include functional verification for targeted cell delivery through the characterization of novel synaptic connections and the functionalities of transported and transplanted cells. The success of the Mag-Neurobot opens up new avenues of research and application; it offers a test platform for functional neural connections and neural regenerative processes through cell transplantation.

Validation of a novel path planner for stereotactic neurosurgical interventions-A retrospective clinical study

BACKGROUND

The gold standard workflow for targeting structures in the brain involves manual path planning. This preoperative manual path planning is very time-intensive and laborious, especially when some outcome measures such as maximum ablation and penetration depth has to be optimised.

METHODS

Our novel path planner generates an optimal path which maximises the hippocampus penetration and distance from critical structures using a precomputed cost map and a reward map.

RESULTS

The average penetration ratio for 12 cases is 88.13 ± 23.23% for a resolution of 1° and a safety margin of 1 mm. Average run time for the path planner based on 1° resolution was 1.99 ± 0.68 min.

CONCLUSIONS

Results show that the algorithm can generate safe and clinically relevant paths with a quantitative representation of the penetration depth and is faster than the average reported time for manual path planning.

Deep brain-machine interfaces: sensing and modulating the human deep brain

Different from conventional brain-machine interfaces that focus more on decoding the cerebral cortex, deep brain-machine interfaces enable interactions between external machines and deep brain structures. They sense and modulate deep brain neural activities, aiming at function restoration, device control and therapeutic improvements. In this article, we provide an overview of multiple deep brain recording and stimulation techniques that can serve as deep brain-machine interfaces. We highlight two widely used interface technologies, namely deep brain stimulation and stereotactic electroencephalography, for technical trends, clinical applications and brain connectivity research. We discuss the potential to develop closed-loop deep brain-machine interfaces and achieve more effective and applicable systems for the treatment of neurological and psychiatric disorders.

Case Report: Late-Onset Lennox-Gastaut Syndrome Treated With Stereotactic Electroencephalography-Guided Radiofrequency Thermocoagulation Before Craniotomy

The onset of Lennox-Gastaut syndrome (LGS), a severe epilepsy syndrome, is typically before 8 years of age. Late-onset LGS (with onset in adolescence and adulthood) is relatively rare clinically and has some differences from classical LGS. Herein, we describe the case of a patient with late-onset LGS and provide a literature review of such cases. The patient had focal epilepsy onset at 8 years of age. After a 9-year evolution, he suffered seizures of different types and had a diagnosis of late-onset LGS. Drug treatment was ineffective. Nothing was found on stereotactic electroencephalography (SEEG) and magnetic resonance imaging (MRI) during the course of the disease. After the second presurgical evaluation, we found a suspicious focus on high-resolution structural MRI which was verified by SEEG at last. After SEEG-guided radiofrequency thermocoagulation (RFTC), his seizures were controlled, and his cognitive function and quality of living clearly improved. However, his seizures recurred 2 years later, and he underwent left occipital resection. Thereafter, his seizures have been controlled until now. This case emphasizes the importance of high-resolution structural MRI in the treatment of LGS. Furthermore, it suggests that late-onset LGS may be caused by focal lesions and evolve from focal epilepsy. Thus, characterizing the clinical symptoms and performing individualized electroencephalographic follow-up are both very important. Additionally, the clinical outcome in this case implies the value and limitations of RFTC in patients with epilepsy and a clear focal lesion. Moreover, this case further supports differences between late-onset and classical LGS in terms of clinical manifestation, cognitive changes, prognosis, and treatment.

Delayed hemorrhage after pediatric stereo-electroencephalography: delayed occurrence or delayed diagnosis?

BACKGROUND

Stereo-electroencephalography (SEEG) is a well-known invasive diagnostic method for drug-resistant epilepsy (DRE). Its rate of complications is relatively low, being the intracranial hemorrhage (ICH) the most relevant. Most centers perform immediate imaging studies after SEEG to rule out complications. However, delayed intracranial hemorrhages (DIH) can occur despite normal imaging studies in the immediate postoperative period.

METHODS

We performed a retrospective review of DRE pediatric patients operated on SEEG between April 2016 and December 2020 in our institution. After implantation, an immediate postoperative CT was performed to check electrode placement and rule out acute complications. An additional MRI was performed 24 h after surgery. We collected all postoperative hemorrhages and considered them as major or minor according to Wellmer´s classification.

RESULTS

Overall, 25 DRE patients were operated on SEEG with 316 electrodes implanted. Three ICHs were diagnosed on postoperative imaging. Two of them were asymptomatic requiring no treatment, while the other needed surgical evacuation after clinical worsening. The total risk of hemorrhage per procedure was 12%, but just one third of them were clinically relevant. Two hemorrhages were not visible on immediate postoperative CT, being incidentally diagnosed in the 24 h MRI. We recorded them as DIH and are reported in detail.

CONCLUSION

Few reports of DIH after SEEG exist in the literature. It remains unclear whether these cases are late occurring hemorrhages or immediate postoperative hemorrhages undiagnosed on initial imaging. According to our findings, we recommend to perform additional late postoperative imaging to diagnose these cases and manage them accurately.

Leveraging electrophysiologic correlates of word encoding to map seizure onset zone in focal epilepsy: Task-dependent changes in epileptiform activity, spectral features, and functional connectivity

OBJECTIVE

Verbal memory dysfunction is common in focal, drug-resistant epilepsy (DRE). Unfortunately, surgical removal of seizure-generating brain tissue can be associated with further memory decline. Therefore, localization of both the circuits generating seizures and those underlying cognitive functions is critical in presurgical evaluations for patients who may be candidates for resective surgery. We used intracranial electroencephalographic (iEEG) recordings during a verbal memory task to investigate word encoding in focal epilepsy. We hypothesized that engagement in a memory task would exaggerate local iEEG feature differences between the seizure onset zone (SOZ) and neighboring tissue as compared to wakeful rest ("nontask").

METHODS

Ten participants undergoing presurgical iEEG evaluation for DRE performed a free recall verbal memory task. We evaluated three iEEG features in SOZ and non-SOZ electrodes during successful word encoding and compared them with nontask recordings: interictal epileptiform spike (IES) rates, power in band (PIB), and relative entropy (REN; a functional connectivity measure).

RESULTS

We found a complex pattern of PIB and REN changes in SOZ and non-SOZ electrodes during successful word encoding compared to nontask. Successful word encoding was associated with a reduction in local electrographic functional connectivity (increased REN), which was most exaggerated in temporal lobe SOZ. The IES rates were reduced during task, but only in the non-SOZ electrodes. Compared with nontask, REN features during task yielded marginal improvements in SOZ classification.

SIGNIFICANCE

Previous studies have supported REN as a biomarker for epileptic brain. We show that REN differences between SOZ and non-SOZ are enhanced during a verbal memory task. We also show that IESs are reduced during task in non-SOZ, but not in SOZ. These findings support the hypothesis that SOZ and non-SOZ respond differently to task and warrant further exploration into the use of cognitive tasks to identify functioning memory circuits and localize SOZ.

Invasive Electrophysiology for Circuit Discovery and Study of Comorbid Psychiatric Disorders in Patients With Epilepsy: Challenges, Opportunities, and Novel Technologies

Intracranial electroencephalographic (iEEG) recordings from patients with epilepsy provide distinct opportunities and novel data for the study of co-occurring psychiatric disorders. Comorbid psychiatric disorders are very common in drug-resistant epilepsy and their added complexity warrants careful consideration. In this review, we first discuss psychiatric comorbidities and symptoms in patients with epilepsy. We describe how epilepsy can potentially impact patient presentation and how these factors can be addressed in the experimental designs of studies focused on the electrophysiologic correlates of mood. Second, we review emerging technologies to integrate long-term iEEG recording with dense behavioral tracking in naturalistic environments. Third, we explore questions on how best to address the intersection between epilepsy and psychiatric comorbidities. Advances in ambulatory iEEG and long-term behavioral monitoring technologies will be instrumental in studying the intersection of seizures, epilepsy, psychiatric comorbidities, and their underlying circuitry.

Electrocorticography and stereo EEG provide distinct measures of brain connectivity: implications for network models

Brain network models derived from graph theory have the potential to guide functional neurosurgery, and to improve rates of post-operative seizure freedom for patients with epilepsy. A barrier to applying these models clinically is that intracranial EEG electrode implantation strategies vary by centre, region and country, from cortical grid & strip electrodes (Electrocorticography), to purely stereotactic depth electrodes (Stereo EEG), to a mixture of both. To determine whether models derived from one type of study are broadly applicable to others, we investigate the differences in brain networks mapped by electrocorticography and stereo EEG in a cohort of patients who underwent surgery for temporal lobe epilepsy and achieved a favourable outcome. We show that networks derived from electrocorticography and stereo EEG define distinct relationships between resected and spared tissue, which may be driven by sampling bias of temporal depth electrodes in patients with predominantly cortical grids. We propose a method of correcting for the effect of internodal distance that is specific to electrode type and explore how additional methods for spatially correcting for sampling bias affect network models. Ultimately, we find that smaller surgical targets tend to have lower connectivity with respect to the surrounding network, challenging notions that abnormal connectivity in the epileptogenic zone is typically high. Our findings suggest that effectively applying computational models to localize epileptic networks requires accounting for the effects of spatial sampling, particularly when analysing both electrocorticography and stereo EEG recordings in the same cohort, and that future network studies of epilepsy surgery should also account for differences in focality between resection and ablation. We propose that these findings are broadly relevant to intracranial EEG network modelling in epilepsy and an important step in translating them clinically into patient care.

Gamma-band modulation in the human amygdala during reaching movements

OBJECTIVE

Motor brain-computer interface (BCI) represents a new frontier in neurological surgery that could provide significant benefits for patients living with motor deficits. Both the primary motor cortex and posterior parietal cortex have successfully been used as a neural source for human motor BCI, leading to interest in exploring other brain areas involved in motor control. The amygdala is one area that has been shown to have functional connectivity to the motor system; however, its role in movement execution is not well studied. Gamma oscillations (30-200 Hz) are known to be prokinetic in the human cortex, but their role is poorly understood in subcortical structures. Here, the authors use direct electrophysiological recordings and the classic "center-out" direct-reach experiment to study amygdaloid gamma-band modulation in 8 patients with medically refractory epilepsy.

METHODS

The study population consisted of 8 epilepsy patients (2 men; age range 21-62 years) who underwent implantation of micro-macro depth electrodes for seizure localization and EEG monitoring. Data from the macro contacts sampled at 2000 Hz were used for analysis. The classic center-out direct-reach experiment was used, which consists of an intertrial interval phase, a fixation phase, and a response phase. The authors assessed the statistical significance of neural modulation by inspecting for nonoverlapping areas in the 95% confidence intervals of spectral power for the response and fixation phases.

RESULTS

In 5 of the 8 patients, power spectral analysis showed a statistically significant increase in power within regions of the gamma band during the response phase compared with the fixation phase. In these 5 patients, the 95% bootstrapped confidence intervals of trial-averaged power in contiguous frequencies of the gamma band during the response phase were above, and did not overlap with, the confidence intervals of trial-averaged power during the fixation phase.

CONCLUSIONS

To the authors' knowledge, this is the first time that direct neural recordings have been used to show gamma-band modulation in the human amygdala during the execution of voluntary movement. This work indicates that gamma-band modulation in the amygdala could be a contributing source of neural signals for use in a motor BCI system.

Stereoelectroencephalography versus Subdural Electrode Implantation to Determine Whether Patients with Drug-resistant Epilepsy Are Candidates for Epilepsy Surgery

Epilepsy is a chronic condition that affects about 50 million individuals worldwide. While its challenges are profound, there are increasing instances where antiepileptic drugs (AEDs) fail to provide relief to epileptic manifestations. For these pharmacoresistant cases, epilepsy surgery often is an effective route for treatment. However, the complexity and challenges associated with presurgical evaluations have prevented more widespread utilization of epilepsy surgery in pharmacoresistant cases. While preliminary work-ups and non-invasive diagnostic imaging have allowed for limited identification of the epileptogenic zone (EZ), there is yet to be an established pre-determined algorithm for surgical evaluation of patients with epilepsy. However, two modalities are currently being used for localization of the EZ and in determining candidates for surgery: stereoelectroencephalography (SEEG) and subdural electrodes (SDEs). SDE has been used in the United States for decades; however, SEEG now provides a less invasive option for mapping brain regions. We seek to address which intracranial monitoring technique is superior. Through a review of the outcomes of various clinical studies, SEEG was found to have greater safety and efficiency benefits than SDE, such as lower morbidity rates, lower prevalence of neurological deficits, and shorter recovery times. Moreover, SEEG was also found to have further functional benefits by allowing for deeper targeting of cerebral tissue along with bilateral hemispheric monitoring. This has led to increased rates of seizure freedom and control among SEEG patients. Nevertheless, further studies on the limitations and advancements of SEEG and SDE are still required to provide a more comprehensive understanding regarding their application.

Gray Matter Sampling Differences Between Subdural Electrodes and Stereoelectroencephalography Electrodes

Objective: Stereoelectroencephalography (SEEG) has seen a recent increase in popularity in North America; however, concerns regarding the spatial sampling capabilities of SEEG remain. We aimed to quantify and compare the spatial sampling of subdural electrode (SDE) and SEEG implants.

Methods: Patients with drug-resistant epilepsy who underwent invasive monitoring were included in this retrospective case-control study. Ten SEEG cases were compared with ten matched SDE cases based on clinical presentation and pre-implantation hypothesis. To quantify gray matter sampling, MR and CT images were coregistered and a 2.5mm radius sphere was superimposed over the center of each electrode contact. The estimated recording volume of gray matter was defined as the cortical voxels within these spherical models. Paired t-tests were performed to compare volumes and locations of SDE and SEEG recording. A Ripley's K-function analysis was performed to quantify differences in spatial distributions.

Results: The average recording volume of gray matter by each individual contact was similar between the two modalities. SEEG implants sampled an average of 20% more total gray matter, consisted of an average of 17% more electrode contacts, and had 77% more of their contacts covering gray matter within sulci. Insular coverage was only achieved with SEEG. SEEG implants generally consist of discrete areas of dense local coverage scattered across the brain; while SDE implants cover relatively contiguous areas with lower density recording.

Significance: Average recording volumes per electrode contact are similar for SEEG and SDE, but SEEG may allow for greater overall volumes of recording as more electrodes can be routinely implanted. The primary difference lies in the location and distribution of gray matter than can be sampled. The selection between SEEG and SDE implantation depends on sampling needs of the invasive implant.

Edge deep learning for neural implants: a case study of seizure detection and prediction

Objective.Implanted devices providing real-time neural activity classification and control are increasingly used to treat neurological disorders, such as epilepsy and Parkinson's disease. Classification performance is critical to identifying brain states appropriate for the therapeutic action (e.g. neural stimulation). However, advanced algorithms that have shown promise in offline studies, in particular deep learning (DL) methods, have not been deployed on resource-restrained neural implants. Here, we designed and optimized three DL models or edge deployment and evaluated their inference performance in a case study of seizure detection.Approach.A deep neural network (DNN), a convolutional neural network (CNN), and a long short-term memory (LSTM) network were designed and trained with TensorFlow to classify ictal, preictal, and interictal phases from the CHB-MIT scalp EEG database. A sliding window based weighted majority voting algorithm was developed to detect seizure events based on each DL model's classification results. After iterative model compression and coefficient quantization, the algorithms were deployed on a general-purpose, off-the-shelf microcontroller for real-time testing. Inference sensitivity, false positive rate (FPR), execution time, memory size, and power consumption were quantified.Main results.For seizure event detection, the sensitivity and FPR for the DNN, CNN, and LSTM models were 87.36%/0.169 h^-1, 96.70%/0.102 h^-1, and 97.61%/0.071 h^-1, respectively. Predicting seizures for early warnings was also feasible. The LSTM model achieved the best overall performance at the expense of the highest power. The DNN model achieved the shortest execution time. The CNN model showed advantages in balanced performance and power with minimum memory requirement. The implemented model compression and quantization achieved a significant saving of power and memory with an accuracy degradation of less than 0.5%.Significance.Inference with embedded DL models achieved performance comparable to many prior implementations that had no time or computational resource limitations. Generic microcontrollers can provide the required memory and computational resources, while model designs can be migrated to application-specific integrated circuits for further optimization and power saving. The results suggest that edge DL inference is a feasible option for future neural implants to improve classification performance and therapeutic outcomes.

Deep anomaly detection of seizures with paired stereoelectroencephalography and video recordings

Real-time seizure detection is a resource intensive process as it requires continuous monitoring of patients on stereoelectroencephalography. This study improves real-time seizure detection in drug resistant epilepsy (DRE) patients by developing patient-specific deep learning models that utilize a novel self-supervised dynamic thresholding approach. Deep neural networks were constructed on over 2000 h of high-resolution, multichannel SEEG and video recordings from 14 DRE patients. Consensus labels from a panel of epileptologists were used to evaluate model efficacy. Self-supervised dynamic thresholding exhibited improvements in positive predictive value (PPV; difference: 39.0%; 95% CI 4.5–73.5%; Wilcoxon–Mann–Whitney test; N = 14; p = 0.03) with similar sensitivity (difference: 14.3%; 95% CI − 21.7 to 50.3%; Wilcoxon–Mann–Whitney test; N = 14; p = 0.42) compared to static thresholds. In some models, training on as little as 10 min of SEEG data yielded robust detection. Cross-testing experiments reduced PPV (difference: 56.5%; 95% CI 25.8–87.3%; Wilcoxon–Mann–Whitney test; N = 14; p = 0.002), while multimodal detection significantly improved sensitivity (difference: 25.0%; 95% CI 0.2–49.9%; Wilcoxon–Mann–Whitney test; N = 14; p < 0.05). Self-supervised dynamic thresholding improved the efficacy of real-time seizure predictions. Multimodal models demonstrated potential to improve detection. These findings are promising for future deployment in epilepsy monitoring units to enable real-time seizure detection without annotated data and only minimal training time in individual patients.

Unexpected pain with electrocortical stimulation in a teenager with temporal encephalocele

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Temporal encephalocele is a treatable cause of drug-resistant epilepsy.

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Stereo-EEG can better localize seizure onset and identify potential post-op deficits.

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We present a neurophysiologic illustration of an important anatomic relationship.

Temporal lobe encephalocele has emerged as a potentially unrecognized cause of drug-resistant temporal lobe epilepsy (TLE) that can be effectively treated with epilepsy surgery. Here we present a case in which a 17-year-old male with drug-resistant epilepsy and left temporal encephalocele underwent workup for epilepsy surgery, and experienced unexpected pain with electrocortical stimulation. Stimulation of stereo-EEG electrodes in the left temporal pole resulted in severe, unilateral left-sided facial pain due to inadvertent stimulation of the trigeminal nerve. Stereo-EEG showed seizure onset adjacent to encephalocele with no involvement of mesial temporal structures. A temporal pole resection sparing the mesial temporal structures and repair of the sphenoid bone defect was performed. The patient experienced post-operative seizure freedom, with no loss of language function or sensory deficits in the distribution of the trigeminal nerve. This case highlights temporal encephalocele as a potentially overlooked cause of TLE and underscores the anatomical proximity of the trigeminal nerve to the temporal pole, an important consideration for surgical planning.

Sharp decrease in the Laplacian matrix rank of phase-space graphs: a potential biomarker in epilepsy

In this paper, phase space reconstruction from stereo-electroencephalography data of ten patients with focal epilepsy forms a series of graphs. Those obtained graphs reflect the transition characteristics of brain dynamical system from pre-seizure to seizure of epilepsy. Interestingly, it is found that the rank of Laplacian matrix of these graphs has a sharp decrease when a seizure is close to happen, which thus might be viewed as a new potential biomarker in epilepsy. In addition, the reliability of this method is numerically verified with a coupled mass neural model. In particular, our simulation suggests that this potential biomarker can play the roles of predictive effect or delayed awareness, depending on the bias current of the Gaussian noise. These results may give new insights into the seizure detection.

On the Use of Digital Subtraction Angiography in Stereoelectroencephalography Surgical Planning to Prevent Collisions with Vessels

OBJECTIVE

Stereoelectroencephalography (SEEG) consists of the implantation of microelectrodes for the electrophysiological characterization of epileptogenic networks. To reduce a possible risk of intracranial bleeding by vessel rupture during the electrode implantation, the stereotactic trajectories must follow avascular corridors. The use of digital subtraction angiography (DSA) for vascular visualization during planning is controversial due to the additional risk related to this procedure. Here we evaluate the utility of this technique for planning when the neurosurgeon has it available together with gadolinium-enhanced T1-weighted magnetic resonance sequence (T1-Gd) and computed tomography angiography (CTA).

METHODS

Twenty-two implantation plans for SEEG were initially done using T1-Gd imaging (251 trajectories). DSA was only used later during the revision process. In 6 patients CTA was available at this point as well. We quantified the position of the closest vessel to the trajectory in each of the imaging modalities.

RESULTS

Two thirds of the trajectories that appeared vessel free in the T1-Gd or CTA presented vessels in their proximity, as shown by DSA. Those modifications only required small shifts of both the entry and target point, so the diagnostic aims were preserved.

CONCLUSIONS

T1-Gd and CTA, despite being the most commonly used techniques for SEEG planning, frequently fail to reveal vessels that are dangerously close to the trajectories. Higher-resolution vascular imaging techniques, such as DSA, can provide the neurosurgeon with crucial information about vascular anatomy, resulting in safer plans.

Accuracy and Safety of Customized Stereotactic Fixtures for Stereoelectroencephalography in Pediatric Patients

Stereoelectroencephalography (SEEG) in children with intractable epilepsy presents particular challenges. Their thin and partially ossified cranium, specifically in the temporal area, is prone to fracture while attaching stereotactic systems to the head or stabilizing the head in robot's field of action. Postponing SEEG in this special population of patients can have serious consequences, reducing their chances of becoming seizure-free and impacting their social and cognitive development. This study demonstrates the safety and accuracy offered by a frameless personalized 3D printed stereotactic implantation system for SEEG investigations in children under 4 years of age. SEEG was carried out in a 3-year-old patient with drug-resistant focal epilepsy, based on a right temporal-perisylvian epileptogenic zone hypothesis. Fifteen intracerebral electrodes were placed using a StarFix patient-customized stereotactic fixture. The median lateral entry point localization error of the electrodes was 0.90 mm, median lateral target point localization error was 1.86 mm, median target depth error was 0.83 mm, and median target point localization error was 1.96 mm. There were no perioperative complications. SEEG data led to a tailored right temporal-insular-opercular resection, with resulting seizure freedom (Engel IA). In conclusion, patient-customized stereotactic fixtures are a safe and accurate option for SEEG exploration in young children.

Individualized stereoelectroencephalography evaluation and navigated resection in medically refractory pediatric epilepsy

Pediatric patients frequently require invasive exploration with intracranial electrodes to achieve high-resolution delineation of the epileptogenic zones (EZ). We intend to discuss the efficacy and safety of stereoelectroencephalophraphy (SEEG) monitoring in pediatric patients with difficulty to localize the EZ. We retrospectively analyzed presurgical findings, SEEG data, resections, and outcomes of a series of 72 consecutive pediatric patients (<18 yrs) who had medically refractory epilepsy and received SEEG recording between January 2015 and September 2019. There were 20 girls and 52 boys with a mean age of 10.13 ± 4.11 years old (range: 1.8-18 years). Twenty-seven patients (37.5%) had nonlesional magnetic resonance imagings (MRIs). In total, 744 electrodes were implanted for an average of 10.33 ± 2.53 (range: 3-18) electrodes per patient. Twenty-eight explorations were unilateral (17 left and 11 right), and 44 explorations were bilateral (12 of which was predominately one side). The average monitoring period in days for the SEEG was 8.99 ± 5.79 (range: 3-25) days. The EZ could be located in 67 (94.4%) patients for the initial implantation according to SEEG monitoring. Lobectomy was performed in 12 patients (17.9%), of those anterior temporal lobectomy (ATL) was performed in 8 cases (11.9%) and insular plus was 2 cases (3.0%), multilobectomy resections in 15 cases (22.4%), tailored cortical resections in 37 cases (55.2%), and corpus callosotomy plus in 2 cases (3.0%). The average follow-up was 18.1 ± 7.53 months (range: 6-54). Forty-three of 67 patients (64.2%) were Engel class I, 12 patients (17.9%) were Engel class II, 10 patients (14.9%) were Engel class III, and an additional 2 patients (3.0%) were Engel class IV. In the SEEG implantation series, no child experienced serious or permanent morbidity. One patient (1.4%) experienced symptomatic intracranial hemorrhage (ICH), and 3 patients (4.2%) experienced asymptomatic ICH. There were no postimplantation infections or other postoperative complications associated with the SEEG. Several common complications related to resection surgery were included in this series with zero mortality. Of the 6 patients in whom we performed a second surgery, 4 of them subsequently became seizure-free (66.7%) after undergoing the second resection with SEEG evaluation. Stereoelectroencephalophraphy is a safe and efficient methodology to identify the EZ in particularly complex cases of focal medically refractory epilepsy for pediatric patients, even in infancy and early childhood. Seizure outcomes of SEEG-guided resection surgery are desirable. We recommend SEEG evaluations and even a more aggressive resection in certain pediatric patients who failed initial resection with realistic chances to benefit from reoperation.

Innovations in 3-Dimensional Tissue Models of Human Brain Physiology and Diseases

3-dimensional (3D) laboratory tissue cultures have emerged as an alternative to traditional 2-dimensional (2D) culture systems that do not recapitulate native cell behavior. The discrepancy between in vivo and in vitro tissue-cell-molecular responses impedes understanding of human physiology in general and creates roadblocks for the discovery of therapeutic solutions. Two parallel approaches have emerged for the design of 3D culture systems. The first is biomedical engineering methodology, including bioengineered materials, bioprinting, microfluidics and bioreactors, used alone or in combination, to mimic the microenvironments of native tissues. The second approach is organoid technology, in which stem cells are exposed to chemical and/or biological cues to activate differentiation programs that are reminiscent of human (prenatal) development. This review article describes recent technological advances in engineering 3D cultures that more closely resemble the human brain. The contributions of in vitro 3D tissue culture systems to new insights in neurophysiology, neurological diseases and regenerative medicine are highlighted. Perspectives on designing improved tissue models of the human brain are offered, focusing on an integrative approach merging biomedical engineering tools with organoid biology.

Detection of Electrophysiological Activity of Amygdala during Anesthesia Using Stereo-EEG: A Preliminary Research in Anesthetized Epileptic Patients

Recent studies of anesthesia mechanisms have focused on neuronal network and functional connectivity. The stereo-electroencephalography (SEEG) recordings provide appropriate temporal and spatial resolution to study whole-brain dynamics; however, the feasibility to detect subcortical signals during anesthesia still needs to be studied with clinical evidence. Here, we focus on the amygdala to investigate if SEEG can be used to detect cortical and subcortical electrophysiological activity in anesthetized epileptic patients. Therefore, we present direct evidence in humans that SEEG indeed can be used to record cortical and subcortical electrophysiological activity during anesthesia. The study was carried out in propofol-anesthetized five epileptic patients. The electrophysiology activity of the amygdala and other cortical areas from anesthesia to the recovery of consciousness was investigated using stereo-EEG (SEEG). Results indicated that with the decrease of propofol concentration, power spectral density (PSD) in the delta band of the amygdala significantly decreased. When it was close to recovery, the correlation between the amygdala and ipsilateral temporal lobe significantly decreased followed by a considerable increase when awake. The findings of the current study suggest SEEG as an effective tool for providing direct evidence of the anesthesia mechanism.

Utility of hybrid PET/MRI multiparametric imaging in navigating SEEG placement in refractory epilepsy

PURPOSE

Stereo-electroencephalography (SEEG) implantation before epilepsy surgery is critical for precise localization and complete resection of the seizure onset zone (SOZ). Combined metabolic and morphological imaging using hybrid PET/MRI may provide supportive information for the optimization of the SEEG coverage of brain structures. In this study, we originally imported PET/MRI images into the SEEG positioning system to evaluate the application of PET/MRI in guiding SEEG implantation in refractory epilepsy patients.

MATERIALS

Forty-two patients undergoing simultaneous PET/MRI examinations were recruited. All the patients underwent SEEG implantation guided by hybrid PET/MRI and surgical resection or ablation of epileptic lesion. Surgery outcome was assessed using a modified Engel classification one year (13.60 ± 2.49 months) after surgery. Areas of SOZ were identified using hybrid PET/MRI and concordance with SEEG was evaluated. Logistic regression analysis was used to predict the presence of a favorable outcome with the coherence of concordance of PET/MRI and SEEG.

RESULTS

Hybrid PET/MRI (including visual PET, MRI, plus MI Neuro) identified SOZ lesions in 38 epilepsy patients (90.47 %). PET/MRI showed the same SOZ localization with SEEG in 29 patients (69.05 %), which was considered to be concordant. The concordance between the PET/MRI and SEEG findings was significantly predictive of a successful surgery outcome (odds ratio = 20.41; 95 % CI = 2.75-151.4, P = 0.003**).

CONCLUSION

Hybrid PET/MRI combined visual PET, multiple sequences MRI and SPM PET helps identify epilepsy lesions particularly in subtle hypometabolic areas. Patients with concordant epileptic lesion localization on PET/MRI and SEEG demonstrated a more favorable outcome than those with inconsistent localization between modalities.

Proceedings of the Seventh Annual Deep Brain Stimulation Think Tank: Advances in Neurophysiology, Adaptive DBS, Virtual Reality, Neuroethics and Technology

The Seventh Annual Deep Brain Stimulation (DBS) Think Tank held on September 8th of 2019 addressed the most current: (1) use and utility of complex neurophysiological signals for development of adaptive neurostimulation to improve clinical outcomes; (2) Advancements in recent neuromodulation techniques to treat neuropsychiatric disorders; (3) New developments in optogenetics and DBS; (4) The use of augmented Virtual reality (VR) and neuromodulation; (5) commercially available technologies; and (6) ethical issues arising in and from research and use of DBS. These advances serve as both "markers of progress" and challenges and opportunities for ongoing address, engagement, and deliberation as we move to improve the functional capabilities and translational value of DBS. It is in this light that these proceedings are presented to inform the field and initiate ongoing discourse. As consistent with the intent, and spirit of this, and prior DBS Think Tanks, the overarching goal is to continue to develop multidisciplinary collaborations to rapidly advance the field and ultimately improve patient outcomes.

Optimized stereoelectroencephalography-guided radiofrequency thermocoagulation in the treatment of patients with focal epilepsy

Epilepsy is a severe health disorder affecting people of all ages with high prevalence worldwide. The introduction of new antiepileptic drugs has yielded notable effects in recent decades, yet there are still approximately 30% of patients with seizures refractory to medical therapy. Open surgical resection is widely accepted as a highly effective approach for the treatment of drug-resistant focal epilepsy if the epileptogenic zone can be precisely delineated. However, concerns about the impact of open surgery on brain function have driven considerable interest in less invasive techniques. Clinically, stereoelectroencephalography (SEEG) offers a unique means of exploring the pathophysiologic process and accurately mapping the epileptogenic network in presurgical evaluations for patients with epilepsy because of insufficient information from other noninvasive investigations. Moreover, SEEG-guided radiofrequency thermocoagulation (SEEG-guided RF-TC), which ablates lesions directly through the recording electrodes according to electroclinical evidence, has emerged as a promising, minimally invasive modality with notable preservation of neurocognitive functions. This critical review summarizes the technical details of the parameters and the selection of patients for SEEG-guided RF-TC based on the literature as well as our experiences. With respect to the parameters, the power and duration of RF-TC are discussed. In particular, an optimized SEEG-guided RF-TC modality that integrates more contacts from multiple different electrodes to create a confluent lesioning field is proposed for a more curative effect in comparison to the current protocol of palliative treatment in which RF-TC selectively disrupts critical hubs in the epileptic network through contiguous contacts within the range of a single electrode. Currently, SEEG-guided RF-TC is indicated for a variety of small, deeply seeded and well-demarcated epileptogenic foci, such as deep heterotopic nodules and hypothalamic hamartoma. The efficacy of treating patients with focal cortical dysplasias in the eloquent cortex and with mesial temporal lobe epilepsy associated with hippocampal sclerosis needs to be further determined. Given the small number of patients reported, randomized controlled trials are necessary to compare the efficacy of SEEG-guided RF-TC with conventional methods in the future.